30+ Mobile Games

Architected and built a real-time analytics platform backend in AWS using Golang servers, Spark Structured Streaming, and Databricks (Apache Spark/Hive/Parquet) for 30+ mobile gaming titles with considerations for security, monitoring, and data governance best practices.

Built a robust data ingestion and ETL pipeline for 100+ internal and third party data sources using a scalable Apache Airflow cluster and Databricks in AWS to support the growing needs of the Data Science and User Acquisition teams.

Personal Projects

An analytics dashboard and JSON API for viewing aggregate download stats on python packages available on pypi.org via Google BigQuery.

Built in Python 3 using Flask, Celery, and redis with plotly.js for visualization, GitHub OAuth for user authentication, and PostgreSQL backend. Deployed to AWS Elastic Beanstalk using Docker and Supervisor.

A fully automated twitch.tv stream controller and twitch chat bot for spectating live games of highly ranked League of Legends players with proficiency on a single in-game character (One-Trick Ponies) using data provided by the Riot Games API.

Written in Python3 with asyncio, aiohttp, and pywinauto running on Windows 7 and broadcasting with OBS Studio and the League of Legends spectator client.